手指静脉图像恢复中皮肤散射抑制的扩散光学模型

Wenhao You, Weikang Zhou, Jing Huang, Yaqin Liu, Feng Yang, Ziyu Chen
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引用次数: 1

摘要

基于手指静脉的人体识别由于具有较高的识别精度,已被广泛应用于多个领域。然而,由于手指组织的强散射导致的图像退化不可避免地降低了识别率。本文提出了一种新的方法来解决手指静脉成像中的皮肤散射问题。首先,提出了一种新的扩散点扩散函数(diffusion- psf)模型来精确描述手指组织中的光散射。其次,利用Stein's无偏风险估计(fuzzy - sure)方法对扩散- psf模型参数进行了精确估计。最后,我们采用多重wiener SURE-LET(线性扩展阈值)方法来提高恢复性能的鲁棒性。实验结果表明,该方法显著提高了手指静脉图像的清晰度,增强了静脉网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A diffusion optical model for skin scattering suppression in finger vein image restoration
Human identification using finger vein has been adopted in number of fields due to its high accuracy of recognition. However, image degradation caused by the strong scattering of finger tissues inevitably reduces the recognition rate. In this paper, we propose a new method to address the skin scattering problems in finger vein imaging. Firstly, a novel diffusion Point Spread Function (diffusion-PSF) model is proposed to precisely describe light scattering in finger tissues. Secondly, the blur-SURE (Stein's unbiased risk estimate) method is utilized to yield accurate estimation of the diffusion-PSF model's parameters. Finally, we adopt the multi-Wiener SURE-LET (Linear expansion thresholds) approach to improve the robustness of restoration performance. The experimental results illustrate that the proposed method significantly improves the clarity of finger vein images and enhances the venous network.
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